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Diffstat (limited to 'python/pyarmnn/examples/tests/test_style_transfer.py')
-rw-r--r-- | python/pyarmnn/examples/tests/test_style_transfer.py | 70 |
1 files changed, 70 insertions, 0 deletions
diff --git a/python/pyarmnn/examples/tests/test_style_transfer.py b/python/pyarmnn/examples/tests/test_style_transfer.py new file mode 100644 index 0000000000..fae4a427f0 --- /dev/null +++ b/python/pyarmnn/examples/tests/test_style_transfer.py @@ -0,0 +1,70 @@ +# Copyright © 2022 Arm Ltd and Contributors. All rights reserved. +# SPDX-License-Identifier: MIT + +import os +import cv2 +import numpy as np + +from context import style_transfer +from context import cv_utils + + +def test_style_transfer_postprocess(test_data_folder): + content_image = "messi5.jpg" + target_shape = (1,256,256,3) + keep_aspect_ratio = False + image = cv2.imread(os.path.join(test_data_folder, content_image)) + original_shape = image.shape + preprocessed_image = cv_utils.preprocess(image, np.float32, target_shape, False, keep_aspect_ratio) + assert preprocessed_image.shape == target_shape + + postprocess_image = style_transfer.style_transfer_postprocess(preprocessed_image, original_shape) + assert postprocess_image.shape == original_shape + + +def test_style_transfer(test_data_folder): + style_predict_model_path = os.path.join(test_data_folder, "style_predict.tflite") + style_transfer_model_path = os.path.join(test_data_folder, "style_transfer.tflite") + backends = ["CpuAcc", "CpuRef"] + delegate_path = os.path.join(test_data_folder, "libarmnnDelegate.so") + image = cv2.imread(os.path.join(test_data_folder, "messi5.jpg")) + + style_transfer_executor = style_transfer.StyleTransfer(style_predict_model_path, style_transfer_model_path, + image, backends, delegate_path) + + assert style_transfer_executor.get_style_predict_executor_shape() == (1, 256, 256, 3) + +def test_run_style_transfer(test_data_folder): + style_predict_model_path = os.path.join(test_data_folder, "style_predict.tflite") + style_transfer_model_path = os.path.join(test_data_folder, "style_transfer.tflite") + backends = ["CpuAcc", "CpuRef"] + delegate_path = os.path.join(test_data_folder, "libarmnnDelegate.so") + style_image = cv2.imread(os.path.join(test_data_folder, "messi5.jpg")) + content_image = cv2.imread(os.path.join(test_data_folder, "basketball1.png")) + + style_transfer_executor = style_transfer.StyleTransfer(style_predict_model_path, style_transfer_model_path, + style_image, backends, delegate_path) + + stylized_image = style_transfer_executor.run_style_transfer(content_image) + assert stylized_image.shape == content_image.shape + + +def test_create_stylized_detection(test_data_folder): + style_predict_model_path = os.path.join(test_data_folder, "style_predict.tflite") + style_transfer_model_path = os.path.join(test_data_folder, "style_transfer.tflite") + backends = ["CpuAcc", "CpuRef"] + delegate_path = os.path.join(test_data_folder, "libarmnnDelegate.so") + + style_image = cv2.imread(os.path.join(test_data_folder, "messi5.jpg")) + content_image = cv2.imread(os.path.join(test_data_folder, "basketball1.png")) + detections = [(0.0, [0.16745174, 0.15101701, 0.5371381, 0.74165875], 0.87597656)] + labels = {0: ('person', (50.888902345757494, 129.61878417939724, 207.2891028294508)), + 1: ('bicycle', (55.055339686943654, 55.828708219750574, 43.550389695374676)), + 2: ('car', (95.33096265662336, 194.872841553212, 218.58516479057758))} + style_transfer_executor = style_transfer.StyleTransfer(style_predict_model_path, style_transfer_model_path, + style_image, backends, delegate_path) + + stylized_image = style_transfer.create_stylized_detection(style_transfer_executor, 'person', content_image, + detections, 720, labels) + + assert stylized_image.shape == content_image.shape |